Language and terminology give people authority and creates negotiation power. The AI industry understands this. That's why terms like agents and automation get thrown around so loosely.
Most of what people call agents are just structured workflows that help with very specific tasks. Jumping straight to full automation is why most AI projects fail (cough, cough).
Start with augmentation
Your team has deep expertise and judgment that AI can't replicate. What AI can do is make them dramatically more effective at what they already do well.
We start by removing friction from their daily work. If your analysts spend hours pulling data from multiple sources, we build tools that gather and structure that information instantly. If diligence requires reading through hundreds of documents, we create systems that extract key points and flag potential issues. Your team still makes the decisions. They're just making them faster and with better information.
Earn your way to automation
Once we understand your workflows deeply, we can introduce more capability. We call this working our way up the totem pole. Earning each level of trust and capability with you before moving to the next.
Each layer of automation requires proof that the previous layer works reliably. Your team needs to trust the outputs. You need to understand the edge cases. We need to know how the system performs under real conditions.
Eventually, what began with helping your analysts extract data evolves into a system that supports entire phases of your investment process. But the path there is gradual, built on strong foundations that make those systems last.